(1) #127 Bowdoin (13-6)

1062.31 (30)

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# Opponent Result Effect Opp. Delta % of Ranking Status Date Event
130 Bates College Win 11-10 5.72 25 4.82% Counts Mar 26th Layout Pigout 2022
270 Bentley Win 15-6 2.37 17 4.82% Counts (Why) Mar 26th Layout Pigout 2022
291 Haverford Win 14-9 -9.23 47 4.82% Counts Mar 26th Layout Pigout 2022
291 Haverford** Win 15-5 0 47 0% Ignored (Why) Mar 27th Layout Pigout 2022
187 Rowan Win 13-10 5.34 43 5.11% Counts Apr 2nd Northeast Classic
180 Wesleyan Win 11-7 14.56 35 4.97% Counts Apr 2nd Northeast Classic
189 Vermont-C Win 11-6 15.57 53 4.83% Counts (Why) Apr 2nd Northeast Classic
241 SUNY-Albany Win 13-5 10.41 42 5.11% Counts (Why) Apr 3rd Northeast Classic
120 Connecticut Win 13-12 9.3 40 5.11% Counts Apr 3rd Northeast Classic
119 Yale Loss 12-13 -4.14 53 5.11% Counts Apr 3rd Northeast Classic
32 Middlebury Loss 7-15 -4.36 28 5.73% Counts (Why) Apr 17th North New England D III College Mens CC 2022
257 Colby Win 15-5 6.07 37 5.73% Counts (Why) Apr 17th North New England D III College Mens CC 2022
130 Bates College Loss 9-10 -8.34 25 5.73% Counts Apr 17th North New England D III College Mens CC 2022
130 Bates College Win 10-9 7.76 25 6.44% Counts Apr 30th New England D III College Mens Regionals 2022
118 Brandeis Loss 9-13 -25.2 7 6.44% Counts Apr 30th New England D III College Mens Regionals 2022
171 Bryant Loss 7-9 -27.7 20 5.91% Counts Apr 30th New England D III College Mens Regionals 2022
130 Bates College Loss 10-15 -32.04 25 6.44% Counts May 1st New England D III College Mens Regionals 2022
270 Bentley Win 15-3 3.22 17 6.44% Counts (Why) May 1st New England D III College Mens Regionals 2022
171 Bryant Win 13-3 30.13 20 6.44% Counts (Why) May 1st New England D III College Mens Regionals 2022
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FAQ

The results on this page ("USAU") are the results of an implementation of the USA Ultimate Top 20 algorithm, which is used to allocate post season bids to both colleg and club ultimate teams. The data was obtained by scraping USAU's score reporting website. Learn more about the algorithm here. TL;DR, here is the rating function. Every game a team plays gets a rating equal to the opponents rating +/- the score value. With all these data points, we iterate team ratings until convergence. There is also a rule for discounting blowout games (see next FAQ)
For reference, here is handy table with frequent game scrores and the resulting game value:
"...if a team is rated more than 600 points higher than its opponent, and wins with a score that is more than twice the losing score plus one, the game is ignored for ratings purposes. However, this is only done if the winning team has at least N other results that are not being ignored, where N=5."

Translation: if a team plays a game where even earning the max point win would hurt them, they can have the game ignored provided they win by enough and have suffficient unignored results.